Binxin Ru
Cited by
Cited by
How powerful are performance predictors in neural architecture search?
C White, A Zela, R Ru, Y Liu, F Hutter
Advances in Neural Information Processing Systems 34, 28454-28469, 2021
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
B Ru, X Wan, X Dong, M Osborne
ICLR 2021, 2020
Bayesian optimisation over multiple continuous and categorical inputs
B Ru, A Alvi, V Nguyen, MA Osborne, S Roberts
International Conference on Machine Learning, 8276-8285, 2020
BayesOpt Adversarial Attack
R Binxin, C Adam, B Arno, Y Gal
International Conference on Learning Representations, 2020
Neural architecture search: Insights from 1000 papers
C White, M Safari, R Sukthanker, B Ru, T Elsken, A Zela, D Dey, F Hutter
arXiv preprint arXiv:2301.08727, 2023
Think global and act local: Bayesian optimisation over high-dimensional categorical and mixed search spaces
X Wan, V Nguyen, H Ha, B Ru, C Lu, MA Osborne
arXiv preprint arXiv:2102.07188, 2021
Fast Information-theoretic Bayesian Optimisation
B Ru, M McLeod, D Granziol, MA Osborne
International Conference on Machine Learning (ICML) 2018, 2018
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
AS Alvi, B Ru, J Calliess, SJ Roberts, MA Osborne
International Conference on Machine Learning (ICML) 2019, 2019
Speedy Performance Estimation for Neural Architecture Search
B Ru, C Lyle, L Schut, M van der Wilk, Y Gal
Advances in Neural Information Processing Systems, 2021, 2021
Neural architecture generator optimization
R Ru, P Esperanca, FM Carlucci
Advances in Neural Information Processing Systems 33, 12057-12069, 2020
A bayesian perspective on training speed and model selection
C Lyle, L Schut, R Ru, Y Gal, M van der Wilk
Advances in neural information processing systems 33, 10396-10408, 2020
Adversarial attacks on graph classifiers via bayesian optimisation
X Wan, H Kenlay, R Ru, A Blaas, MA Osborne, X Dong
Advances in Neural Information Processing Systems 34, 6983-6996, 2021
On redundancy and diversity in cell-based neural architecture search
X Wan, B Ru, PM Esperanša, Z Li
arXiv preprint arXiv:2203.08887, 2022
Bayesian generational population-based training
X Wan, C Lu, J Parker-Holder, PJ Ball, V Nguyen, B Ru, M Osborne
International conference on automated machine learning, 14/1-27, 2022
MEMe: An accurate maximum entropy method for efficient approximations in large-scale machine learning
D Granziol, B Ru, S Zohren, X Dong, M Osborne, S Roberts
Entropy 21 (6), 551, 2019
Approximate neural architecture search via operation distribution learning
X Wan, B Ru, PM Esparanša, FM Carlucci
Proceedings of the IEEE/CVF Winter Conference on Applications of Computerá…, 2022
Dha: End-to-end joint optimization of data augmentation policy, hyper-parameter and architecture
K Zhou, L Hong, S Hu, F Zhou, B Ru, J Feng, Z Li
arXiv preprint arXiv:2109.05765, 2021
Learning to identify top elo ratings: A dueling bandits approach
X Yan, Y Du, B Ru, J Wang, H Zhang, X Chen
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8797-8805, 2022
Towards discovering neural architectures from scratch
S Schrodi, D Stoll, B Ru, RS Sukthanker, T Brox, F Hutter
Construction of hierarchical neural architecture search spaces based on context-free grammars
S Schrodi, D Stoll, B Ru, R Sukthanker, T Brox, F Hutter
Advances in Neural Information Processing Systems 36, 2024
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